Conversational Semantic

Conversational semantic parsing focuses on translating natural language utterances within a conversation into formal, machine-executable representations, such as API calls or SQL queries, enabling computers to understand and respond to complex, multi-turn interactions. Current research emphasizes improving the accuracy and efficiency of these translations, particularly by addressing challenges like constraint violations in API calls, effectively modeling conversational context using graph neural networks or dynamic context graphs, and mitigating issues like model instability during retraining. These advancements are crucial for building more robust and natural-feeling conversational AI systems across various applications, from virtual assistants to knowledge-based question answering.